|
Download README.md from BeyzaTopbas/Project-Digit-Recognizer: direct link, hf CLI and curl.
- Browser
- Download file 584 Bytes
-
https://huggingface.co/spaces/BeyzaTopbas/Project-Digit-Recognizer/resolve/main/README.md
- Command line
-
hf download hf://spaces/BeyzaTopbas/Project-Digit-Recognizer/README.md
-
curl -L -o README.md https://huggingface.co/spaces/BeyzaTopbas/Project-Digit-Recognizer/resolve/main/README.md
584 Bytes
| title: Project Digit Recognizer | |
| emoji: π | |
| colorFrom: red | |
| colorTo: red | |
| sdk: docker | |
| app_port: 8501 | |
| tags: | |
| - streamlit | |
| pinned: false | |
| short_description: Streamlit template space | |
| # π’ Digit Recognizer App | |
| This Streamlit application predicts handwritten digits using a machine learning model trained on the MNIST dataset. | |
| ## π How it works | |
| 1. Upload an image of a digit | |
| 2. The image is converted to 28x28 grayscale | |
| 3. The model predicts the digit | |
| ## π€ Model | |
| - Random Forest Classifier | |
| - Accuracy: ~96% | |
| ## π Tech Stack | |
| - Scikit-learn | |
| - Streamlit | |
| - Hugging Face Spaces |